Gesture detection systems are increasingly used in natural user interfaces to interact with computing devices without the need for physical input devices such as keyboards, mice, stylus pens and the like and without the need to touch a screen. For example, game systems are available where a player is able to stand in front of a depth and color camera system which captures images of the player making gestures such as golf swings, dance moves, and hand gestures such as hand waving, pushing motions and pulling motions. Complex analysis of the captured images is computed to detect and recognize the gestures and the results are used to influence game play.
There is an ongoing need to improve the accuracy of gesture detection systems. There is also an ongoing need to develop gesture detection systems which have low observational latency. Here latency means the number of frames that a gesture detection system consumes before recognizing an underlying gesture depicted in those frames. Existing gesture detection systems typically have a relatively high observational latency which makes the natural user interface harder to use by the game player or other end user. Where observational latency is high errors may result in use of the natural user interface. For example, conflicting inputs may be made to a game or other system where gesture recognition input is delayed and becomes conflicted with other forms of user input made without delay. Where natural user interface technology is used for medical applications, for example, to control robotic equipment for surgery or other applications requiring fine grained control, it is especially important to reduce observational latency with regard to gesture detection.
The embodiments described below are not limited to implementations which solve any or all of the disadvantages of known gesture detection systems.